SOWCompact: A federated process mining method for social workflows

Rojo, Javier; Garcí­a-Alonso, José; Berrocal, Javier; Hernández, Juan; Murillo, Juan Manuel; Canal, Carlos

doi:10.1016/j.ins.2022.02.035

Cited by 6 publications

(4 citation statements)

References 32 publications

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“…The user (activity) models were extracted using a Heuristic miner. Using the evaluation technique by Rojo et al [111], the study achieved a result that was similar to the result achieved by [111], where the authors extracted core social workflows from activities of daily living data using a specified weight. In this study, all relevant activities were retrieved with a weight of 0.4.…”

Section: Discussionmentioning

confidence: 56%

“…Using Heuristic miner, the user (activity) models were extracted from digital activity datasets. Using the evaluation technique by Rojo et al [111], the study achieved a result that was similar to the approach used by Rojo et al [111], whereby relevant activities were obtained at a particular arc weight. Therefore, the first practical contribution of the study is the extraction of the activity model as specific incorporation of user models.…”

Section: Practical Contributionsmentioning

confidence: 80%

“…The significant advantage of the heuristic miner is the ability to deal with nonlocal dependencies, short loops, and noisy data while extracting a correct model. Rojo et al [111] incorporated a heuristic miner in the activity extraction of smart home residents, and it has been proven to be efficient in modelling smart home residents' activity models.…”

Section: Activity Modellingmentioning

confidence: 99%

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The PBC Model: Supporting Positive Behaviours in Smart Environments

Adewoyin

Wesson

Vogts

2022

Sensors

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Several behavioural problems exist in office environments, including resource use, sedentary behaviour, cognitive/multitasking, and social media. These behavioural problems have been solved through subjective or objective techniques. Within objective techniques, behavioural modelling in smart environments (SEs) can allow the adequate provision of services to users of SEs with inputs from user modelling. The effectiveness of current behavioural models relative to user-specific preferences is unclear. This study introduces a new approach to behavioural modelling in smart environments by illustrating how human behaviours can be effectively modelled from user models in SEs. To achieve this aim, a new behavioural model, the Positive Behaviour Change (PBC) Model, was developed and evaluated based on the guidelines from the Design Science Research Methodology. The PBC Model emphasises the importance of using user-specific information within the user model for behavioural modelling. The PBC model comprised the SE, the user model, the behaviour model, classification, and intervention components. The model was evaluated using a naturalistic-summative evaluation through experimentation using office workers. The study contributed to the knowledge base of behavioural modelling by providing a new dimension to behavioural modelling by incorporating the user model. The results from the experiment revealed that behavioural patterns could be extracted from user models, behaviours can be classified and quantified, and changes can be detected in behaviours, which will aid the proper identification of the intervention to provide for users with or without behavioural problems in smart environments.

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Section: Discussionmentioning

confidence: 56%

Section: Practical Contributionsmentioning

confidence: 80%

Section: Activity Modellingmentioning

confidence: 99%

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The PBC Model: Supporting Positive Behaviours in Smart Environments

Adewoyin

Wesson

Vogts

2022

Sensors

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“…Health processes have an activity sequence that aims to diagnose, treat and avoid potential diseases to enhance patients’ wellness. These processes may include both clinical and nonclinical activities, which are performed by various resources such as doctors, clerks and nurses, and can change for each organization (Rojo et al , 2022; Mans et al , 2015). Distinguishing development possibilities in the health care processes can support to overcome waiting times, increasing the service quality and decrease overcrowding (Vathy-Fogarassy et al , 2022; Konrad et al , 2013).…”

Section: Related Workmentioning

confidence: 99%

Process mining based on patient waiting time: an application in health processes

Doğan

2022

IJWIS

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Purpose Similar to many business processes, waiting times are also essential for health care processes, especially in obstetrics and gynecology outpatient department (GOD), because pregnant women may be affected by long waiting times. Since creating process models manually presents subjective and nonrealistic flows, this study aims to meet the need of an objective and realistic method. Design/methodology/approach In this study, the authors investigate time-related bottlenecks in both departments for different doctors by process mining. Process mining is a pragmatic analysis to obtain meaningful insights through event logs. It applies data mining techniques to business process management with more comprehensive perspectives. Process mining in this study enables to automatically create patient flows to compare considering each department and doctor. Findings The study concludes that average waiting times in the GOD are higher than obstetrics outpatient department. However, waiting times in departments can change inversely for different doctors. Research limitations/implications The event log was created by expert opinions because activities in the processes had just starting timestamp. The ending time of activity was computed by considering the average duration of the corresponding activity under a normal distribution. Originality/value This study focuses on administrative (nonclinical) health processes in obstetrics and GOD. It uses a parallel activity log inference algorithm (PALIA) to produce process trees by handling duplicate activities. Infrequent information in health processes can have critical information about the patient. PALIA considers infrequent activities in the event log to extract meaningful information, in contrast to many discovery algorithms.

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A self-sustainable opportunistic solution for emergency detection in ageing people living in rural areas

et al. 2023

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There are contexts where communication with TCP/IP protocol is not possible due to the lack of infrastructure or a reliable and continuous data transmission. In this cases, alternatives such as Opportunistic Networks (OPPNets) are valid. Such challenging conditions are common in rural areas and are a significant obstacle for the deployment of eHealth technologies for older adults. Considering this context, the present work introduces Interest-based System for Communication in Isolated Areas (ISCA), an OPPNet architecture for remote monitoring and emergency detection in ageing people who live alone. For this, the energetic requirements are considered, providing efficient and sustainable operation. The proposal makes use of a routing algorithm based on interests which enables asynchronous communication among entities. ISCA is evaluated over a realistic scenario and compared with similar state-of-the-art solutions. Experimental results show that ISCA notably improves the delivery probability with an enhancement of 52.25% in comparison to the second best alternative and provides a suitable average latency. Moreover, it also achieves better performance in terms of overhead and hops number compared to the other studied protocols

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SOWCompact: A federated process mining method for social workflows

Cited by 6 publications

References 32 publications

The PBC Model: Supporting Positive Behaviours in Smart Environments

The PBC Model: Supporting Positive Behaviours in Smart Environments

Process mining based on patient waiting time: an application in health processes

A self-sustainable opportunistic solution for emergency detection in ageing people living in rural areas

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